<p>Visualization applications--like flight simulators and virtual reality environments--use geographic information systems to represent actual terrain. Applications like these impose stringent restrictions on acceptable performance and response time. Sequential methods do not meet these requirements, but parallel methods can. The authors are developing a high-performance GIS on an SGI Challenge, a 16-processor machine with a shared address space architecture. They describe how they parallelized a key GIS operation using a message-passing algorithm. As part of the GIS project, the authors evaluated the effect of parallelizing an important GIS operation: range query. They parallelized range query using data partitioning (to reduce synchronization) and dynamic load balancing (to improve speedup). They found these approaches do achieve the performance required for many GIS applications. The approach described here links two diverse approaches to the design of parallel architectures and algorithms. Parallel architectures have emphasized either shared address space or message passing; algorithms either the PRAM or message-passing models. The authors advocate a different link between the architecture and algorithms--their range query operation uses a message-passing algorithm, yet is appropriate for a SASA architecture. </p>